我有一个关于随时间观察到的个体的信息数据库。无论何时记录，我都想找到一种方法来获取这些人的年龄。假设BIRTH指定的值为0，我希望获得之后访问的年龄(以天或月为单位(。获得每个人的最终年龄(天或月(也很有帮助(*不包括在代码中(。例如，ID(A(的最终年龄为10个月。我想使用lubridate函数，因为它的内置日期功能使处理日期更容易。如有任何帮助，我们将不胜感激。
date<-c("2000-01-01","2000-01-14","2000-01-25","2000-02-12","2000-02-27","2000-06-05","2000-10-30",
"2001-02-04","2001-06-15","2001-12-26","2002-05-22","2002-06-04",
"2000-01-08","2000-07-11","2000-08-18","2000-11-27")
ID<-c("A","A","A","A","A","A","A",
"B","B","B","B","B",
"C","C","C","C")
status<-c("BIRTH","ETC","ETC","ETC","ETC","ETC","ETC",
"BIRTH","ETC","ETC","ETC","ETC",
"BIRTH","ETC","ETC","ETC")
df1<-data.frame(date,ID,status)
print(df1)
date ID status
1 2000-01-01 A BIRTH
2 2000-01-14 A ETC
3 2000-01-25 A ETC
4 2000-02-12 A ETC
5 2000-02-27 A ETC
6 2000-06-05 A ETC
7 2000-10-30 A ETC
8 2001-02-04 B BIRTH
9 2001-06-15 B ETC
10 2001-12-26 B ETC
11 2002-05-22 B ETC
12 2002-06-04 B ETC
13 2000-01-08 C BIRTH
14 2000-07-11 C ETC
15 2000-08-18 C ETC
16 2000-11-27 C ETC
date.new<-c("2000-01-01","2000-01-14","2000-01-25","2000-02-12","2000-02-27","2000-06-05","2000-10-30",
"2001-02-04","2001-06-15","2001-12-26","2002-05-22","2001-02-04",
"2000-01-08","2000-07-11","2000-08-18","2000-11-27")
ID.new<-c("A","A","A","A","A","A","A",
"B","B","B","B","B",
"C","C","C","C")
status.new<-c("BIRTH","ETC","ETC","ETC","ETC","ETC","ETC",
"BIRTH","ETC","ETC","ETC","ETC",
"BIRTH","ETC","ETC","ETC")
age<-c(0,1,1,2,2,6,10,
0,4,10,15,16,
0,6,7,10)
df2<-data.frame(date.new,ID.new,status.new,age)
print(df2)
date.new ID.new status.new age
1 2000-01-01 A BIRTH 0
2 2000-01-14 A ETC 1
3 2000-01-25 A ETC 1
4 2000-02-12 A ETC 2
5 2000-02-27 A ETC 2
6 2000-06-05 A ETC 6
7 2000-10-30 A ETC 10
8 2001-02-04 B BIRTH 0
9 2001-06-15 B ETC 4
10 2001-12-26 B ETC 10
11 2002-05-22 B ETC 15
12 2001-02-04 B ETC 16
13 2000-01-08 C BIRTH 0
14 2000-07-11 C ETC 6
15 2000-08-18 C ETC 7
16 2000-11-27 C ETC 10
对于以年或月为单位的与年龄相关的计算，我鼓励您尝试时钟包，而不是lubridate。lubridate是一个很棒的软件包，但如果你不能100%确定自己在做什么，那么通过这些计算会产生一些意想不到的结果。在时钟中，执行此操作的函数是date_count_between()。请注意，clock和lubridate之间的结果之一不同：
library(clock)
library(lubridate, warn.conflicts = FALSE)
library(dplyr, warn.conflicts = FALSE)
df <- tibble(
date = c("2000-01-01","2000-01-14",
"2000-01-25","2000-02-12","2000-02-27","2000-06-05",
"2000-10-30","2001-02-04","2001-06-15","2001-12-26",
"2002-05-22","2002-06-04","2000-01-08","2000-07-11",
"2000-08-18","2000-11-27"),
ID = c("A","A","A","A","A","A",
"A","B","B","B","B","B","C","C","C","C"),
status = c("BIRTH","ETC","ETC","ETC",
"ETC","ETC","ETC","BIRTH","ETC","ETC","ETC","ETC",
"BIRTH","ETC","ETC","ETC")
)
df %>%
mutate(date = date_parse(date)) %>%
group_by(ID) %>%
mutate(birth_date = date[status == "BIRTH"]) %>%
ungroup() %>%
mutate(
age_clock = date_count_between(birth_date, date, "month"),
age_lubridate = as.period(date - birth_date) %/% months(1))
#> # A tibble: 16 × 6
#> date ID status birth_date age_clock age_lubridate
#> <date> <chr> <chr> <date> <int> <dbl>
#> 1 2000-01-01 A BIRTH 2000-01-01 0 0
#> 2 2000-01-14 A ETC 2000-01-01 0 0
#> 3 2000-01-25 A ETC 2000-01-01 0 0
#> 4 2000-02-12 A ETC 2000-01-01 1 1
#> 5 2000-02-27 A ETC 2000-01-01 1 1
#> 6 2000-06-05 A ETC 2000-01-01 5 5
#> 7 2000-10-30 A ETC 2000-01-01 9 9
#> 8 2001-02-04 B BIRTH 2001-02-04 0 0
#> 9 2001-06-15 B ETC 2001-02-04 4 4
#> 10 2001-12-26 B ETC 2001-02-04 10 10
#> 11 2002-05-22 B ETC 2001-02-04 15 15
#> 12 2002-06-04 B ETC 2001-02-04 16 15
#> 13 2000-01-08 C BIRTH 2000-01-08 0 0
#> 14 2000-07-11 C ETC 2000-01-08 6 6
#> 15 2000-08-18 C ETC 2000-01-08 7 7
#> 16 2000-11-27 C ETC 2000-01-08 10 10
时钟上说2001-02-04到2002-06-04是16个月，而这里的lubridate方法只说是15个月。这与lubridate计算使用平均月的长度有关，这并不总是准确反映我们对月的看法。
举个简单的例子，我想大多数人都会同意，在二月的这个日子出生的孩子被认为是"；1个月零1天"；老的但卢布里达显示0个月！
library(clock)
library(lubridate, warn.conflicts = FALSE)
# "1 month and 1 day apart"
feb <- as.Date("2020-02-28")
mar <- as.Date("2020-03-29")
# As expected when thinking about age in months
date_count_between(feb, mar, "month")
#> [1] 1
# Not expected
as.period(mar - feb) %/% months(1)
#> [1] 0
secs_in_day <- 86400
secs_in_month <- as.numeric(months(1))
secs_in_month / secs_in_day
#> [1] 30.4375
# Less than 30.4375 days, so not 1 month
mar - feb
#> Time difference of 30 days
问题是lubridate在计算中使用了平均月的长度，即30.4375天。但这两个日期之间只有30天，所以这不被认为是一个完整的月。
另一方面，时钟使用开始日期的日期分量来确定是否"是"；全月"；是否已通过。换句话说，因为我们已经过了3月28日，时钟决定1个月已经过去，这与我们通常对年龄的看法一致。
使用dplyr和lubridate，我们可以执行以下操作。我们首先将date列转换为日期。然后，我们按ID分组，找到出生日期，并通过一些lubridate魔术计算自该日期以来的月数(请参阅如何使用lubridate包计算两个日期矢量之间的月数，其中一个矢量具有NA值？(。
library(dplyr)
library(lubridate)
df1 %>%
mutate(date = as_date(date)) %>%
group_by(ID) %>%
mutate(birth_date = date[status == "BIRTH"],
age = as.period(date - birth_date) %/% months(1)) %>%
ungroup()
哪个给出：
date ID status birth_date age
<date> <fct> <fct> <date> <dbl>
1 2000-01-01 A BIRTH 2000-01-01 0
2 2000-01-14 A ETC 2000-01-01 0
3 2000-01-25 A ETC 2000-01-01 0
4 2000-02-12 A ETC 2000-01-01 1
5 2000-02-27 A ETC 2000-01-01 1
6 2000-06-05 A ETC 2000-01-01 5
7 2000-10-30 A ETC 2000-01-01 9
8 2001-02-04 B BIRTH 2001-02-04 0
9 2001-06-15 B ETC 2001-02-04 4
10 2001-12-26 B ETC 2001-02-04 10
11 2002-05-22 B ETC 2001-02-04 15
12 2002-06-04 B ETC 2001-02-04 15
13 2000-01-08 C BIRTH 2000-01-08 0
14 2000-07-11 C ETC 2000-01-08 6
15 2000-08-18 C ETC 2000-01-08 7
16 2000-11-27 C ETC 2000-01-08 10
除了一些舍入差异外，这是您的预期输出。请参阅我对您问题的评论。